Designing Cloud Data Platforms
豆瓣
Danil Zburivsky / Lynda Partner
简介
In Designing Cloud Data Platforms, you’ll learn how to integrate data from multiple sources into a single, cloud-based, modern data platform. Drawing on their real-world experiences designing cloud data platforms for dozens of organizations, cloud data experts Danil Zburivsky and Lynda Partner take you through a six-layer approach to creating cloud data platforms that maximizes flexibility and manageability and reduces costs. Starting with foundational principles, you’ll learn how to get data into your platform from different databases, files, and APIs, the essential practices for organizing and processing that raw data, and how to best take advantage of the services offered by major cloud vendors. As you progress past the basics you’ll take a deep dive into advanced topics to get the most out of your data platform, including real-time data management, machine learning analytics, schema management, and more.
what's inside
The tools of different public cloud for implementing data platforms
Best practices for managing structured and unstructured data sets
Machine learning tools that can be used on top of the cloud
Cost optimization techniques